Abstract
We describe how a variety of neural network models might be useful in organizing the scientific data that is accumulating on the neurobehavioral effects of cocaine misuse. Implementation involving backpropagation, adaptive resonance theory, and autoassociative memory models are discussed. These techniques appear to have considerable heuristic value in terms of ordering the neurobehavioral effects of cocaine. They promise to provide a better understanding of how this drug affects such basic cognitive abilities such as executive function, attention, memory, decision making, and impulse control. Such knowledge is essential for designing treatment programs that can capitalize on the individual's current cognitive and behavioral assets at each stage of recovery, thereby facilitating the recovery process.
Original language | English (US) |
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Pages | 86-90 |
Number of pages | 5 |
State | Published - 1999 |
Externally published | Yes |
Event | International Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA Duration: Jul 10 1999 → Jul 16 1999 |
Other
Other | International Joint Conference on Neural Networks (IJCNN'99) |
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City | Washington, DC, USA |
Period | 7/10/99 → 7/16/99 |
ASJC Scopus subject areas
- Software
- Artificial Intelligence